Introduction: Chemical disasters occur continuously around the world, but it is not easy to respond quickly when the causative substance is unknown. It is possible to estimate the substance through information, documents, and labeling, but it is limited to chemical accidents within the company or in vehicles that are labeled with substance information, so it is difficult to identify substance information in real time in chemical terrorism, illegal chemical production, and chemical warfare. Therefore, this study investigated systems that estimate chemical substances based on symptoms and applied representative substances in practice. Methods: In this study, the international status and development of symptom-based chemical accident causative agent estimation systems that can be analyzed were investigated through the literature and internet searches. After analyzing 400 chemical accidents for five years through the Comprehensive Chemical Information System, eight substances were selected after excluding duplicate chemicals. Symptoms of exposure to these eight substances were analyzed through WISER. Results: Representative systems include Chemical Companion and Toxicology Information Center, and WISER was ahead in providing probabilistic estimates of chemicals through symptoms. Estimation through artificial intelligence was under research and not applied in practice. Symptom analysis of exposure through WISER can be summarized into 17 typical symptoms. Conclusion: As there are existing contents such as emergency medical information databases and response scenarios for symptoms and medical consequences of chemical accidents, it is expected that the foundation of the causative agent estimation system can be secured by utilizing existing contents and technologies such as artificial intelligence in the future.
S. Wang (Sun,) studied this question.